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The contrastive study of prediction of women's heptathlon performance based on grey theory and BP neural network prediction model

机译:基于灰色理论和BP神经网络预测模型的女子七项全能成绩对比研究

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By adopting literature consultation the data from the scores of successive women???s heptathlon champions during the 23rd to 30thOlympicGames, this paper, based on the scores of the women??? heptathlon champions during the 23rd to 29th Olympic Games, respectively establishes the Grey Forecasting Model and the BP Neural Network Prediction Model, and predicts the scores of the women??? heptathlon champion of the 30thOlympic Games.Meanwhile, this paper also compares the predictionwith the actual value of these twomodels of the scores of thewomen??? heptathlon champion of the 30th Olympic Games, and analyzes these two models??? forecast precision.According to the result, prediction of theGrey ForecastingModel was 6572, and its errorwas 5.5%.And prediction of the BPNeuralNetwork Prediction Model was 6967, and its error was 0.18%. However, on the whole, the Grey ForecastingModel gives better fitting degree to data. The model precision was first grade, and the Grey Model is much fitter to prediction of scores of the women??? heptathlon champion of the Olympic Games.
机译:通过文献研究,从第23届到第30届奥运会比赛中历届女子七项全能冠军的得分数据为基础,本文基于这些女子的得分?在23至29届奥运会上,七项全能冠军分别建立了灰色预测模型和BP神经网络预测模型,并预测了女子得分。同时,本文还将这两种模型的预测值与妇女得分的实际值进行了比较。??第30届奥运会七项全能冠军,并分析了这两种模型???结果表明,灰色预测模型的预测值为6572,其误差为5.5%; BP神经网络预测模型的预测为6967,其误差为0.18%。但是,总体而言,灰色预测模型可以更好地拟合数据。模型的精度是一年级的,而灰色模型则更适合预测女性的分数???奥运会的七项全能冠军。

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